In a typical radio communications system, user communications terminals referred to as user equipment units (UEs) communicate via a radio access network (RAN) with other networks like the Internet. The radio access network (RAN) covers a geographical area which is divided into cell areas, with each cell area being served by a base station, e.g., a radio base station (RBS), which in some networks is also called a “NodeB” or enhanced Node B. A cell is a geographical area where radio coverage is provided by the radio base station equipment at a base station site.
Third Generation (3G) cellular radio systems like Universal Mobile Telecommunications System (UMTS) operating in Wideband Code Division Multiple Access (WCDMA) use different types of radio channels including unscheduled radio channels and scheduled radio channels. Mixed voice/data, circuit/packet switched 3G systems evolved from voice-centric, circuit-switched second generation (2G) systems. Unscheduled channels, sometimes called dedicated channels, are usually allocated to only one user for the duration of a connection carrying information only associated with that one user. Scheduled channels are packet-switched channels over which packets for multiple user connections are carried. Fourth generation (4G) systems, like the Long Term Evolution (LTE) of UMTS and Worldwide Interoperability for Microwave Access (WiMAX), design the air interface based on packet data. Dedicated traffic channels are eliminated in favor of scheduled radio channels in order to simplify the system. Medium access control is thus migrating towards a request resource-grant resource paradigm. In response to actual requests to transmit data from and/or to a user equipment (UE) in the uplink and/or the downlink, the scheduler in the base station dynamically allocates radio resources to satisfy the quality of service requirements associated with the type of data traffic to be transmitted, and at the same time, tries to optimize the system capacity.
The IEEE 802.16 Working Group on Broadband Wireless Access Standards develops formal specifications for the global deployment of broadband Wireless Metropolitan Area Networks (MAN). Although the 802.16 family of standards is officially called WirelessMAN, it is often referred to as WiMAX. In general, 802.16 standardizes two aspects of the air interface: the physical layer (PHY) and the Media Access Control layer (MAC). For the physical layer, one mode of IEEE 802.16e uses scalable orthogonal frequency division multiple access (OFDMA) to support channel bandwidths of between 1.25 MHz and 20 MHz with up to 2048 sub-carriers. IEEE 802.16e supports adaptive modulation and coding, so that in good radio signal conditions, a highly efficient 64 QAM coding scheme can be used, whereas in poor radio signal conditions, a more robust BPSK coding mechanism can be used. In intermediate conditions, 16 QAM and QPSK can be employed. Other physical layer features include support for multiple-in-multiple-out (MIMO) antennas in order to provide good NLOS (Non-line-of-sight) characteristics (or higher bandwidth) and Hybrid automatic repeat request (HARQ) for good error correction performance. Multi-antenna techniques can significantly increase the data rates and reliability of a wireless communication system. The performance is in particular improved if both the transmitter and the receiver use multiple antennas resulting in a multiple-input multiple-output (MIMO) communication channel.
Thus, an important part of LTE and other wireless systems (e.g., IEEE 802.16e and 802.11n) is the support of MIMO antenna deployments and MIMO related processing techniques. A problem in MIMO systems is how to perform accurate channel estimation and noise correlation estimation of the MIMO channels. Assume a MIMO communications using M transmit antennas and N receive antennas, where M is an integer greater than or equal to 1 and N is an integer greater than 1. Channel estimation for the M×N single-input/single-output channels may be determined using an individual channel estimator to estimate each single-input/single-output channel from each transmit antenna to each receive antenna. In this case, each individual channel estimator uses one received signal at the receive antenna. Each such estimator works under the assumption that the noise at the receive antennas is a spatially uncorrelated white noise. But when the noise is not white and/or is correlated, then it must be accounted for in the channel estimation process. In fact, correlated interference at the receive antennas may be used to improve the quality of MIMO channel estimates.
In a cellular type radio system, the noise at the receive antennas includes thermal noise and other-cell interference. Although the focus in this case is on the latter component, the unqualified term “noise” includes both. FIG. 1 shows a simple example of a two base station MIMO system 10 in which a serving base station 12 with four transmit antennas transmits desired information including known pilot symbols to a user equipment (UE) 16 that has two receive antennas ARX1 and ARX2. Transmissions from another interfering base station 14 serving an adjacent cell are also received at the UE's antennas and interfere with the desired signals from base station 12. Although thermal noise present at the two UE antennas is a spatial-temporal white noise, the other cell interference is spatially highly correlated. In FIG. 1, this is represented by the two signals from the interfering base station 14 presenting essentially the same interference I at both of the receive antennas ARX1 and ARX2 at the UE. This spatial correlation can be exploited in the channel estimation process.
But correlated interference at the receive antennas is a problem when it comes to estimating the MIMO channels between a base station and a mobile radio station/user equipment (UE). The M×N single-input/single-output channel estimates depend on the received signals, the known pilot symbols, and also on the noise-plus-interference. The difficulty is that the noise-plus-interference is unknown and its estimate depends on the unknown M×N channel estimates. Hence, there is a “chicken and egg” problem where the M×N channel estimates cannot be determined without accurately knowing the noise-plus-interference, and the noise-plus-interference cannot be determined without accurately knowing the M×N channel estimates.